CN105765605A - Method for determining a relative gradient of a roadway - Google Patents
Method for determining a relative gradient of a roadway Download PDFInfo
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- CN105765605A CN105765605A CN201480054474.2A CN201480054474A CN105765605A CN 105765605 A CN105765605 A CN 105765605A CN 201480054474 A CN201480054474 A CN 201480054474A CN 105765605 A CN105765605 A CN 105765605A
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- 238000000034 method Methods 0.000 title claims abstract description 27
- 238000009434 installation Methods 0.000 claims description 8
- 238000005516 engineering process Methods 0.000 claims description 7
- 239000003550 marker Substances 0.000 claims description 7
- 238000002372 labelling Methods 0.000 claims description 4
- 229910052704 radon Inorganic materials 0.000 claims description 3
- SYUHGPGVQRZVTB-UHFFFAOYSA-N radon atom Chemical compound [Rn] SYUHGPGVQRZVTB-UHFFFAOYSA-N 0.000 claims description 3
- 238000001454 recorded image Methods 0.000 abstract 1
- 238000005452 bending Methods 0.000 description 9
- 230000003068 static effect Effects 0.000 description 4
- 230000003044 adaptive effect Effects 0.000 description 3
- 230000003028 elevating effect Effects 0.000 description 3
- 230000000007 visual effect Effects 0.000 description 3
- 230000008901 benefit Effects 0.000 description 2
- 230000001419 dependent effect Effects 0.000 description 2
- 230000000694 effects Effects 0.000 description 2
- 238000013459 approach Methods 0.000 description 1
- 230000004888 barrier function Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 239000003344 environmental pollutant Substances 0.000 description 1
- 239000002360 explosive Substances 0.000 description 1
- 239000000446 fuel Substances 0.000 description 1
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Classifications
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W40/00—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models
- B60W40/02—Estimation or calculation of non-directly measurable driving parameters for road vehicle drive control systems not related to the control of a particular sub unit, e.g. by using mathematical models related to ambient conditions
- B60W40/06—Road conditions
- B60W40/076—Slope angle of the road
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V10/00—Arrangements for image or video recognition or understanding
- G06V10/40—Extraction of image or video features
- G06V10/48—Extraction of image or video features by mapping characteristic values of the pattern into a parameter space, e.g. Hough transformation
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
- G06V20/00—Scenes; Scene-specific elements
- G06V20/50—Context or environment of the image
- G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
- G06V20/588—Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W50/00—Details of control systems for road vehicle drive control not related to the control of a particular sub-unit, e.g. process diagnostic or vehicle driver interfaces
- B60W2050/0001—Details of the control system
- B60W2050/0043—Signal treatments, identification of variables or parameters, parameter estimation or state estimation
- B60W2050/006—Interpolation; Extrapolation
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2420/00—Indexing codes relating to the type of sensors based on the principle of their operation
- B60W2420/40—Photo, light or radio wave sensitive means, e.g. infrared sensors
- B60W2420/403—Image sensing, e.g. optical camera
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- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Multimedia (AREA)
- Mathematical Physics (AREA)
- Mechanical Engineering (AREA)
- Transportation (AREA)
- Automation & Control Theory (AREA)
- Traffic Control Systems (AREA)
- Image Analysis (AREA)
- Navigation (AREA)
- Image Processing (AREA)
Abstract
The invention relates to a method for determining the gradient of a roadway located at a distance in front of a motor vehicle relative to the roadway section being travelled over by the motor vehicle, wherein images of the roadway located in the front of the motor vehicle are recorded by a camera, route lines in front of the motor vehicle are detected in the recorded images and the relative gradient is calculated on the basis of differences in the direction of the route lines at different distances. According to the invention, the route lines are in each case interpolated in their entirety in a non-linear manner with respect to a horizon (20') of the roadway located at a distance in front of the motor vehicle, wherein the distance between the thus obtained horizon (20') of the route line and a horizon of the roadway section (20) being travelled is calculated, and wherein the relative gradient is calculated on the basis of the distance (D) between the two horizons (20, 20').
Description
A kind of method that the present invention relates to gradient for determining road sections that the road of a distance, motor vehicles front currently travelling relative to motor vehicles, the image of the road in motor vehicles front is wherein recorded by video camera, the image recorded identifies the path-line in motor vehicles front and with reference to the difference in direction of path-line at different distance place to calculate relative inclination, and the invention still further relates to a kind of preamble apparatus for carrying out the method according to independent claims.
In order to meet the corresponding requirements of the current and future requirement of the fuel consumption to the motor vehicles with explosive motor and disposal of pollutants or the energy expenditure to electric vehicle, multiple technology are combined, also include determining relative and absolute road inclination so as to the distance adjusting the vehicle driven relative to front that driving strategy is such as kept by adaptive learning algorithms adapts to road inclination in advance.
The knowledge of relative road inclination can be used for the alignment automatically adjusting other vehicle parameter such as vehicle head lamp road to adapt to front.
Road inclination can use navigation system to obtain from map datum, but, the map datum including road inclination is not that all roads all can be used, and if described data can use, then it is often not as accurate.
Replacement or compensation process for determining relative road inclination can assess the image of the road in motor vehicles front, and described image carrys out record by the video camera in motor vehicles or on motor vehicles.There is such method of feature of the preamble of claim 1 disclosed in EP2051206B1.Described file only considers the difference of the route of the pavement marker two different distances: relatively close motor vehicles and one are in the distance big as far as possible with motor vehicles.Therefore, this method is very easy to make mistakes.
Camera review with reference to their own determines that distance is not very accurate.As an alternative or in addition, distance is also possible to use radar or laser radar to determine, but, expenditure related to this is quite big.
It is an object of the invention to provide a kind of reliable and accurate method for determining relative road inclination and described method is only acted on by assessment camera review.
This purpose is to be realized by the method and apparatus of the preamble according to independent claims.
The advantageous embodiment of the present invention is disclosed in the dependent claims.
According to the present invention, the path-line identified is interpolated with its entirety in each case, wherein said path-line is usually formed continuous lines that is straight or that bend or curve, and described interpolation carries out in a non-linear manner relative to the horizon of the road of a distance, motor vehicles front.Distance between the horizon calculating the road ahead obtained by this way and the horizon of the road sections currently travelled, and directly draw relative inclination from the distance between the two horizon.
In a preferred embodiment, the horizon of the road sections currently travelled is set up by interpolation path line in a linear fashion.In this case, this has the advantage that two horizon distance each other and therefore relative inclination is unrelated with the current pitching of motor vehicles.
The identification of the straight line that the linear interpolation of path-line obtains preferably through Hough transform technique or Radon transform technology.
In the horizontal replacement scheme of the current road sections travelled set up by linear interpolation, the horizon that can also use the installation site by video camera and calibration and set up, wherein needs to consider that the current pitching of motor vehicles and described pitching can use sensors to determine and/or can be determined by the map datum in Vehicular navigation system except the camera after calibration.
Being similar to of the higher order that non-linear interpolation preferably obtains especially by generalized Hough transform technology.
Can using the distance between horizon and the horizon set up by installation site and the calibration of video camera of the road sections currently travelled to determine the current pitching of motor vehicles and/or so that monitoring or the improvement value by the pitch sensor in motor vehicles and/or longitudinal accelerometer delivery, the horizon of the road sections currently travelled is obtained by non-linear interpolation.
The labelling of path-line ordinary representation pavement marker, particularly road edge and/or lane markings, for instance centrage.If such labelling is absent from or in addition, path-line can also pass through other demarcation feature such as anticollision barrier, kerbstones etc. and obtain.
Path-line should essentially continuously reproduce the path that can identify in camera review, at least up the distance substantially limited by the resolution of video camera and the standout of pavement marker.
Then may be used for adjusting driving strategy, vehicle parameter and/or vehicle setting to adapt to road inclination according to the relative inclination that the method calculates.
The following is the exemplary embodiment with reference to accompanying drawing to describe.In the accompanying drawings:
Fig. 1 describes the camera review of the straight road in motor vehicles front in a plane；
Fig. 2 describes the side view of the situation of Fig. 1；
Fig. 3 describes the side view assuming that the road in motor vehicles front comprises situation similar with Fig. 1 when the gradient:
Fig. 4 describes the camera review that the straight road in motor vehicles front of the gradient on direct of travel with increase compares with the situation of Fig. 1；
Fig. 5 a describes the top view of the example of the path-line of the left hand bending of vehicle front；
Fig. 5 b describes the schematic three dimensional views of the path-line assumed in situation figure below 5a that left hand bending extends in the plane identical with the road sections below motor vehicles；
Fig. 5 c describes the schematic three dimensional views of the path-line in situation figure below 5a of the gradient that hypothesis left hand bending tilts upward relative to motor vehicles；
Fig. 5 d describes the schematic camera review of the path-line in Fig. 5 b；
Fig. 5 e describes the schematic camera review of the path-line in Fig. 5 c；
Fig. 6 describes the example of the path-line of the right hand bending in motor vehicles front, and the bending of the described right hand comprises the gradient of increase；And
Fig. 7 describes the flow chart of the example of the method for determining relative road inclination.
Modern motor is provided with the camera chain for supporting security application such as adaptive learning algorithms device, lane-departure warning system or other system more and more continually.Generally assessment uses the image of these camera records to provide the data set of the restriction for application-specific.
For the application, the geometric properties of the geometry of the camera review of the landscape in assessment motor vehicles front, the road sections being about to travel is located therein.
As shown in Figure 1, straight road in one plane characterizes usually by lateral solid line pavement marker 2,2 ' and dotted line centrage 4, solid line pavement marker 2,2 ' and dotted line centrage 4 intersect at a little 6, point 6 is positioned on horizontal line 8, and horizontal line 8 is corresponding to the horizon of real world when the plane travelled.
In camera review, light path and the installation site of video camera is depended in the position in horizon 8.Horizontal line 8 is generally set up after installing video camera and then keeps being permanently fixed.
The side view of situation illustrated in fig. 1 illustrates in fig. 2.Straight road 12 in motor vehicles 10 plane from left to right in the accompanying drawings travels.It is arranged on the windshield of such as motor vehicles 10 video camera 14 below point to direct of travel and on direction of observation 16, observe the horizon of road, such as, horizontal line 8 in Fig. 1, direction of observation 16 is arranged essentially parallel to road 12 extends according to path and the distance that may identify which.The road 12 in motor vehicles 10 front is arranged in the visual field of video camera 14, and wherein in video camera 14 front, the road sections at final distance d place is being different from the direction of observation 18 observing horizontal direction of observation 16 and is observing.
Fig. 3 describe the road 12 assuming immediately below motor vehicles 10 remain the smooth constant slope simply comprising on direct of travel in other words along slope portion 12 ' extend when the situation similar with Fig. 1 side view.In this case, the horizon of slope portion 12 ' is below the horizon of flat road 12, and is observed on direction of observation 16 ' by video camera 14, is different from the direction of observation 16 seeing horizontal line 8 according to the direction of observation 16 ' of the value of the gradient.Road sections is now currently located in the direction of observation 18 of video camera 14, and described road sections is at the distance d ' place in video camera 14 front, and described distance is more than the distance d in Fig. 1.
When gradient rather than the gradient, the described gradient is also designated as negative slope, and the distance of the road sections seen in the same pixel position of the imageing sensor of video camera 14 will become less rather than bigger in identical location of pixels.
Distinguish above-mentioned horizon effect and the effect relevant to the pitching of motor vehicles 10 be necessary, the pitching of motor vehicles 10 dynamically produce due to elevating movement or due to uneven Static Load produce.
Owing to all path-lines in Fig. 1 such as pavement marker 2,2 ' and centrage 4 intersect at a point, the horizon of the road sections therefore observed by video camera 14 can be calculated by camera review, and reason is in that to originate in the path-line interpolation in a linear fashion of display foreground and horizon is that the intersection point by them is drawn.
For this purpose, if path-line is provided as point group, for instance when digital camera image, then identify that straight line is feasible by itself from Hough transform technique well known in the prior art or Radon transform technology.
When straight road in one plane, the horizon 20 in the Fig. 4 obtained by this way should correspond to the preset level line 8 in Fig. 1.In each case, horizon 20 is relevant to the road sections that motor vehicles 10 are currently travelling with horizontal line 8.
Direct of travel has the straight road of the gradient of increase, path-line extends with ever-reduced straight manner, increase with the distance of video camera 14, but described path-line is gradually curved, as shown in Figure 4, and they intersect at the point being positioned on horizon 20 ', and horizon 20 ' extends below distance D in horizon 20.
Additionally, in this case, the horizon 20 identified in offer Fig. 3 of linear interpolation or straight line, because the part closer to the path-line of video camera 14 is almost straight and starts to be interpolated from display foreground.
The horizon 20 ' that the path-line being gradually curved is assembled is relevant to the road sections of a distance, motor vehicles 10 front, namely relevant to the road sections in the scope remaining in identification, identification range substantially standout by the resolution of video camera 14 and road longitudinal direction labelling is limited.This scope is usually several 10 meters, for instance 20 meters.
Point that the path-line that is gradually curved is assembled and therefore horizon 20 ' can the non-linear interpolation of path-line by bending be determined, for instance, determined at the point group place representing path-line by generalized Hough transform technology.
The distance D between two horizon 20 and 20 ' in Fig. 4 represents relative road inclination, in other words, and the gradient of the straight part of the road travelled and away from the difference between the gradient of the road sections of a distance.
In the way of identical with the above, horizon 20 ' also obtains when forming the road of curve of the following stated.
Fig. 5 a describes the top view of the path-line of the example of the road sections of the bending for motor vehicles 10 front, wherein x coordinate is corresponding to path-line or the point group and the video camera 14 distance on the width of motor vehicles 10 that represent these lines, and wherein corresponds to path-line relative to the vertical coordinate of x coordinate compressibility factor 10 or represent point group and the video camera 14 distance on direct of travel of described path-line.
Fig. 5 b is the schematic three dimensional views of the path-line in situation figure below 5a of the left hand bending in the plane that the road sections that road sections is with motor vehicles 10 are currently travelling is identical, and Fig. 5 c be at road sections not only to left hand lateral bend and also constantly tilt also relative to the road sections before it in other words motor vehicles 10 be placed exactly in left hand bending gradient starting point situation figure below 5a in the schematic three dimensional views of path-line.
Fig. 5 d describes the path-line of Fig. 5 b in the visual field from video camera 14 and Fig. 5 e describes the path-line of Fig. 5 c in the visual field from video camera 14.
In Fig. 5 d and 5e, ordinate value 1 represents the horizon that the installation site by video camera 14 and calibration provide, and described horizon is corresponding to the horizon 8 in Fig. 1 or the horizon 20 in Fig. 3.
If it is readily apparent that in Fig. 5 d and 5e, path-line not interpolation in a non-linear manner, then described path-line converges at the some place being positioned on default horizon in figure 5d, for instance intended when road in one plane.But, the path-line in Fig. 5 e converges at the point being positioned on the horizontal line by ordinate value 1.5.
The road curve seen by video camera 14 in Fig. 5 e is directly determined by camera review relative to default horizontal relative inclination.It practice, relative inclination=(the horizontal ordinate value of non-linear interpolation-preset horizontal ordinate value)/preset horizontal ordinate value × 100%=(1.5-1) 1 × 100%=50%.
It should be noted that the relative inclination obtained by this way is not dependent on being difficult to determine or only pass through camera review rather than by video camera geometry to be grossly inaccurate any distance that mode is determined.Distance between the horizon of the horizon of the road sections that motor vehicles 10 are currently travelling and the road of a distance, motor vehicles 10 front is the linear measure of the relative inclination in real world, and described later horizon is obtained by the non-linear interpolation of path-line.
And in the example of fig. 4, the horizon of the road sections that motor vehicles 10 are currently travelling will be obtained by the linear interpolation of path-line, in the example of Fig. 5 e, the horizon preset by the installation site of video camera 14 and calibration will be used for calculating relative inclination.What can use in both approaches is any, but, wherein the first is preferred.
But, calculated in horizontal situation by linear interpolation, it is notable that in each case, this possibly cannot accurately provide the gradient of the road sections that motor vehicles are currently travelling.Such as, if in the example of Fig. 5 e, path-line in a linear fashion interpolation the same as the example of Fig. 4, then will obtain the value of incorrect relative inclination.This exists in the fact that Fig. 5 c and 5e describes the situation lacking actual association, and wherein the road of motor vehicles 10 dead ahead becomes suddenly extreme inclination.Also lead to the soft transition of the inclination of reality in the correctly horizontal line of the road sections that path-line linear interpolation is currently travelling to motor vehicles 10 and therefore cause correct relative inclination.Additionally, when those in such as Fig. 5 c and 5e, the horizon of the road sections that motor vehicles 10 are currently travelling under any circumstance arrives not long ago being correctly identified of position corresponding to Fig. 5 c and 5e at motor vehicles 10.
Fig. 6 describes for being that the right hand curve with reference to motor vehicles 10 front calculates two horizontal other examples by the linearly or nonlinearly interpolation of path-line, and described right hand curve comprises the gradient of increase.If the interpolation in a linear fashion of the path-line in Fig. 6 illustrated by heavy line, then described path-line intersects at the point 22 being positioned on horizon 24, the horizon of the road sections that horizon 24 is currently travelling corresponding to motor vehicles 10.If the interpolation in a non-linear manner of the path-line illustrated by solid line, then described path-line intersects at the point 26 being positioned on horizon 24 ', the horizon of the horizon 24 ' road sections corresponding to detecting and in a distance, motor vehicles 10 front still through video camera 14.
In this case, the ordinate value in the horizon 24 of relative inclination=(ordinate value in the horizon 24 of the ordinate value-linear interpolation in the horizon 24 ' of non-linear interpolation)/linear interpolation.Specifically, in this case, for instance, relative inclination-4% occurs it being the negative sign due to the gradient.
When the relative inclination obtained by this way, adjusting vehicle parameter is feasible to adapt to path on the horizon.Such as, for by regenerative braking recover Vehicular battery electric current, for select another gear, for increase adaptive learning algorithms keep the vehicle relative to traveling ahead distance prepare or start program can carry out.
By the horizon calculating of non-linear interpolation, path-line in one or identical camera review has the advantage that the relative inclination obtained by this way is unrelated with the current pitching of the motor vehicles 10 caused due to elevating movement or uneven load by linear interpolation and another aspect on the one hand.
On the other hand, if motor vehicles 10 pitching, then the horizon preset by the installation site of video camera 14 and calibration is moved.In the scope of said method as described below, the fact that, can be utilized to also by camera review to determine the pitching of motor vehicles 10.
Compare in longer time cycle or road sections if presetting horizon with the horizon determined by the linear interpolation of path-line, then measuring of the pitching of motor vehicles 10 being derived from causing due to static load.
If additionally, preset horizon and compare in longer time cycle or road sections with the horizon determined by the linear interpolation of path-line, then measuring of the pitching of motor vehicles 10 being derived from causing due to dynamic elevating movement.
May be used to the measured value of the pitch sensor in vehicle or longitudinal accelerometer described information more accurately or when being absent from such sensor about the information of the pitching of motor vehicles 10 can directly be used by any equipment that must detect pitching in motor vehicles, described information is obtained by camera review.
Fig. 7 describes the flow chart of the example of the method for determining relative road inclination.When the production process of motor vehicles terminates, video camera is installed in the horizon H0 (step S2) that after such as windshield, (step S1) and calibration are fixed.
Afterwards, when motor vehicles just in motion, the linear interpolation in the step S3 path-line by identifying in camera review carrys out horizontal line H1 definitely, and carrys out horizontal line H2 definitely in step S4 by the non-linear interpolation of path-line described above.
In step S5, calculated the gradient of the road sections that the road in motor vehicles front is currently travelling relative to motor vehicles by two horizon H1 and H2 distance each other.Selectively, if it is known that the absolute tilt degree of the road sections currently travelled such as is merged by map datum and/or any sensor, then the absolute tilt degree of the road in front can also be calculated.
In step S4, if it occur that gradient change, then adjust vehicle parameter or vehicle setting as mentioned above in step S6.
Additionally, the difference between the horizon H0 for good and all calibrated in step s 2 and the horizon H1 determined by the linear interpolation of path-line in step s3 can be screened by short-term and for a long time in the step s 7.
With reference to the short-term difference of two horizon H0 and H1, the vehicle dynamic pitching during handling can be determined in step s 8, and when necessary can in step s 9 with the signal fused of pitch sensor and/or longitudinal accelerometer.
With reference to the long-term difference of two horizon H0 and H1, the static pitching of the vehicle caused due to current loads can be determined in step slo, and the Mass Distribution of vehicle can be determined by described static pitching in step s 11.
Claims (9)
1. the method for the gradient being used for the road sections that the road determining motor vehicles (10) a distance, front is currently travelling relative to described motor vehicles (10), the image of the described road in described motor vehicles (10) front is wherein recorded by video camera (14), the described image in described motor vehicles (10) front recorded identifies path-line (2,2 ', 4) difference and with reference to the direction of the described path-line at different distance place calculates relative inclination
It is characterized in that,
In each case, by described path-line (2,2 ', 4) with its entirety in a non-linear manner relative to the horizon (20 ' of the described road of described motor vehicles (10) a distance, front, 24 ') interpolation is carried out, calculate the horizon (20 ' of the described path-line obtained by this way, 24 ') with the horizon (20 of the described road sections currently travelled, 24) distance between, and calculate described relative inclination by the two horizon described distance (D) each other.
2. method according to claim 1,
It is characterized in that,
Obtaining the described horizon (20,24) of the described road sections currently travelled, wherein said path-line (2,2 ', 4) carries out interpolation in a linear fashion.
3. method according to claim 2,
It is characterized in that,
The described linear interpolation of described path-line (2,2 ', 4) is the identification of the straight line obtained by Hough transform technique or Radon transform technology.
4. method according to claim 1,
It is characterized in that,
The horizon that the described horizon (20,24) of the current described road sections travelled is the installation site by described video camera (14) and calibration and sets up.
5. the method according to any one in aforementioned claim,
It is characterized in that,
Described non-linear interpolation is the approximation of the higher order obtained especially by generalized Hough transform technology.
6. the method according to any one in aforementioned claim,
It is characterized in that,
Use the described horizon (20 ' of the described road sections currently travelled, 24 ') distance between the described horizon and by described installation site and the described calibration of described video camera set up is to determine the current pitching of described motor vehicles (10), and the described horizon of the described road sections currently travelled is obtained by non-linear interpolation.
7. the method according to any one in aforementioned claim,
It is characterized in that,
Described path-line (2,2 ', 4) represents the labelling of pavement marker, particularly road edge and/or lane line.
8. the method according to any one in aforementioned claim,
It is characterized in that,
Described path-line (2,2 ', 4) essentially continuously reproduces the path that may identify which in described camera review.
9. one kind for determining the device of the gradient of road sections that the described road of described motor vehicles (10) a distance, front currently travelling relative to described motor vehicles (10) in the image of the road in motor vehicles (10) front, described image carrys out record by video camera (14)
It is characterized in that,
Described device is designed to perform the method according to any one in aforementioned claim.
Applications Claiming Priority (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE102013220303.9 | 2013-10-08 | ||
| DE102013220303.9A DE102013220303A1 (en) | 2013-10-08 | 2013-10-08 | Method for determining a relative road gradient |
| PCT/EP2014/071393 WO2015052158A2 (en) | 2013-10-08 | 2014-10-07 | Method for determining a relative gradient of a roadway |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN105765605A true CN105765605A (en) | 2016-07-13 |
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Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201480054474.2A Pending CN105765605A (en) | 2013-10-08 | 2014-10-07 | Method for determining a relative gradient of a roadway |
Country Status (6)
| Country | Link |
|---|---|
| US (1) | US10023198B2 (en) |
| EP (1) | EP3055179B1 (en) |
| CN (1) | CN105765605A (en) |
| DE (1) | DE102013220303A1 (en) |
| RU (1) | RU2016101516A (en) |
| WO (1) | WO2015052158A2 (en) |
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| KR102135088B1 (en) * | 2015-07-20 | 2020-07-17 | 엘지전자 주식회사 | Autonomous Driving Vehicle |
| US20180154902A1 (en) | 2016-12-06 | 2018-06-07 | GM Global Technology Operations LLC | Vehicle control using road angle data |
| CN107704801B (en) * | 2017-08-18 | 2021-08-06 | 电子科技大学 | Curve lane line detection method based on segmented straight line and segmented Bezier curve |
| FR3091843B1 (en) * | 2019-01-21 | 2022-02-11 | Psa Automobiles Sa | Method for regulating a speed of a motor vehicle as a function of a slope of a rolling zone to come |
| US11562576B2 (en) * | 2020-08-05 | 2023-01-24 | GM Global Technology Operations LLC | Dynamic adjustment of augmented reality image |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1388028A (en) * | 2001-05-25 | 2003-01-01 | 现代自动车株式会社 | Method for sampling to road information using vehicle-carrying camera and detecting for spaces of vehicles |
| EP1524848A1 (en) * | 2003-10-16 | 2005-04-20 | Hitachi, Ltd. | Imaging apparatus and a camera for vehicles |
| US20060161331A1 (en) * | 2005-01-14 | 2006-07-20 | Denso Corporation | Drive control system for automotive vehicle |
| EP2051206A1 (en) * | 2007-10-17 | 2009-04-22 | Valeo Vision | Method for automatically determining the gradient of a slope about to be entered by an automobile, and associated device |
| CN101800908A (en) * | 2009-02-06 | 2010-08-11 | 通用汽车环球科技运作公司 | Estimate the camera auto-calibration carry out by the horizon |
| CN101922929A (en) * | 2009-06-09 | 2010-12-22 | 财团法人车辆研究测试中心 | Vehicle inclination sensing method and head lamp automatic leveling system applying same |
Family Cites Families (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPH0995194A (en) * | 1995-09-29 | 1997-04-08 | Aisin Seiki Co Ltd | Detecting device for object in front of vehicle |
| DE69731585T2 (en) * | 1996-07-15 | 2005-12-01 | Toyota Jidosha K.K., Toyota | Vehicle driving state predicting device and warning device using the device |
| JP3995846B2 (en) * | 1999-09-24 | 2007-10-24 | 本田技研工業株式会社 | Object recognition device |
| JP3736346B2 (en) * | 2000-12-26 | 2006-01-18 | 日産自動車株式会社 | Lane detection device |
| KR100418763B1 (en) | 2000-12-28 | 2004-02-18 | 현대자동차주식회사 | A method for measuring road slope and a system for controling vehicle speed upon road slope measured thereby |
| WO2008044911A1 (en) * | 2006-10-09 | 2008-04-17 | Tele Atlas B.V. | Method and apparatus for generating an orthorectified tile |
| FR2935520B1 (en) | 2008-08-29 | 2011-10-28 | Valeo Vision Sas | METHOD FOR DETECTING A TARGET OBJECT FOR A MOTOR VEHICLE |
| JP4905512B2 (en) * | 2009-07-09 | 2012-03-28 | 株式会社デンソー | Target information estimation device |
| US20110098922A1 (en) * | 2009-10-27 | 2011-04-28 | Visteon Global Technologies, Inc. | Path Predictive System And Method For Vehicles |
| JP5926080B2 (en) | 2012-03-19 | 2016-05-25 | 株式会社日本自動車部品総合研究所 | Traveling lane marking recognition device and program |
| KR101942527B1 (en) * | 2015-11-09 | 2019-01-25 | 엘지전자 주식회사 | Apparatus for providing around view and Vehicle |
| EP3176013B1 (en) * | 2015-12-01 | 2019-07-17 | Honda Research Institute Europe GmbH | Predictive suspension control for a vehicle using a stereo camera sensor |
-
2013
- 2013-10-08 DE DE102013220303.9A patent/DE102013220303A1/en not_active Withdrawn
-
2014
- 2014-10-07 US US15/023,485 patent/US10023198B2/en active Active
- 2014-10-07 WO PCT/EP2014/071393 patent/WO2015052158A2/en active Application Filing
- 2014-10-07 CN CN201480054474.2A patent/CN105765605A/en active Pending
- 2014-10-07 RU RU2016101516A patent/RU2016101516A/en not_active Application Discontinuation
- 2014-10-07 EP EP14781866.0A patent/EP3055179B1/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN1388028A (en) * | 2001-05-25 | 2003-01-01 | 现代自动车株式会社 | Method for sampling to road information using vehicle-carrying camera and detecting for spaces of vehicles |
| EP1524848A1 (en) * | 2003-10-16 | 2005-04-20 | Hitachi, Ltd. | Imaging apparatus and a camera for vehicles |
| US20060161331A1 (en) * | 2005-01-14 | 2006-07-20 | Denso Corporation | Drive control system for automotive vehicle |
| EP2051206A1 (en) * | 2007-10-17 | 2009-04-22 | Valeo Vision | Method for automatically determining the gradient of a slope about to be entered by an automobile, and associated device |
| CN101800908A (en) * | 2009-02-06 | 2010-08-11 | 通用汽车环球科技运作公司 | Estimate the camera auto-calibration carry out by the horizon |
| CN101922929A (en) * | 2009-06-09 | 2010-12-22 | 财团法人车辆研究测试中心 | Vehicle inclination sensing method and head lamp automatic leveling system applying same |
Non-Patent Citations (1)
| Title |
|---|
| 郑南宁: "《计算机视觉与模式识别》", 31 March 1998 * |
Cited By (17)
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|---|---|---|---|---|
| CN106250880B (en) * | 2016-08-23 | 2020-12-04 | 广西科技大学 | Visual detection method for gradient of road before vehicle uphill |
| CN106250880A (en) * | 2016-08-23 | 2016-12-21 | 广西科技大学 | Road grade visible detection method before a kind of vehicle driving up |
| CN108116409A (en) * | 2016-11-30 | 2018-06-05 | 三星电子株式会社 | For generating the method and apparatus of autonomous driving route |
| CN110770744A (en) * | 2017-06-29 | 2020-02-07 | 大众汽车有限公司 | Device and method for determining properties of a surface in the surroundings of a vehicle |
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| CN109552336A (en) * | 2017-09-26 | 2019-04-02 | 罗伯特·博世有限公司 | Method for obtaining the gradient in lane |
| CN109552336B (en) * | 2017-09-26 | 2024-04-16 | 罗伯特·博世有限公司 | Method for determining the gradient of a roadway |
| CN107697098B (en) * | 2017-09-29 | 2018-08-03 | 金辉 | A kind of compartment gradient in-site measurement platform |
| CN107697098A (en) * | 2017-09-29 | 2018-02-16 | 佘以道 | A kind of measuring method at compartment gradient scene |
| CN109741617A (en) * | 2018-11-12 | 2019-05-10 | 浙江吉利汽车研究院有限公司 | A kind of parking lot is parked air navigation aid and device |
| CN113424240A (en) * | 2019-02-21 | 2021-09-21 | 日立安斯泰莫株式会社 | Travel road recognition device |
| CN113424240B (en) * | 2019-02-21 | 2023-11-17 | 日立安斯泰莫株式会社 | Road identification device |
| CN109883393A (en) * | 2019-03-01 | 2019-06-14 | 杭州晶一智能科技有限公司 | Gradient prediction technique in front of mobile robot based on binocular stereo vision |
| CN109883393B (en) * | 2019-03-01 | 2020-11-27 | 杭州晶一智能科技有限公司 | Method for predicting front gradient of mobile robot based on binocular stereo vision |
| CN109974661A (en) * | 2019-03-11 | 2019-07-05 | 杭州晶一智能科技有限公司 | Gradient prediction technique in front of mobile robot based on depth information |
| CN109848997A (en) * | 2019-03-20 | 2019-06-07 | 杭州晶一智能科技有限公司 | Gradient method for quick predicting in front of mobile robot based on the stereoscopic camera that has a down dip |
| CN109848997B (en) * | 2019-03-20 | 2020-08-04 | 杭州晶一智能科技有限公司 | Rapid prediction method for front slope of mobile robot based on declination stereo camera |
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|---|---|
| US20160214617A1 (en) | 2016-07-28 |
| EP3055179B1 (en) | 2017-08-30 |
| DE102013220303A1 (en) | 2015-04-09 |
| WO2015052158A2 (en) | 2015-04-16 |
| RU2016101516A (en) | 2017-11-15 |
| US10023198B2 (en) | 2018-07-17 |
| WO2015052158A3 (en) | 2015-09-24 |
| EP3055179A2 (en) | 2016-08-17 |
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